Collective Intelligence Coordination and Cooperation in Teamed Part-Time and Full-Time Postgraduates

With the rise of artificial intelligence and high-performance information and computing technologies, as an aftermath of the industry 4.0 mandate, new capabilities have flourished for a more controlled and, to a certain extent, autonomous work-space management. This efficiently links a collection of individuals to exchange information of their inputs (knowledge, expertise, skills, etc.) and outputs (results, outcomes, scores, bonuses, performance, etc.). As an example of this matter, a collective intelligence approach to coordinate the cooperation of teamed part-time (PT) and full-time (FT) postgraduates is presented in this work. The proposition of this behavioral and social computing field as a CI process-of-research and -development is to define PT-FT synergies for the viability of an industrial-like university, where most of the students at the postgraduate level are PT and share academic duties with non-academic tasks. This unprecedented portion of PT students is a challenge to be addressed in the educational process for achieving more productive frameworks to better operate, control, and monitor itself. The cooperation among PT and FT is the key element for a successful overall result, however their coordination must balance the trade-offs and avoid the pitfalls of such CI. This PT-FT cooperation should be in the extent, duration, pace, path, etc., that suits different topics of research and development, students' level of knowledge, or any other feature that can be classified, measured, analyzed, and adjusted. The utilization of social media and work-made platforms are modeled in the PT-FT CI scheme for an optimal individual expertise-platform introduced in this work.